Modeling climate change impact on inflow and hydropower generation of Nangbeto Dam in West Africa using multi-model CORDEX ensemble and ensemble machine learning

Climate change (CC) poses a threat to renewable hydropower, which continues to play a significant role in energy generation in West Africa (WA). Thus, the assessment of the impacts of climate change and climate variability on hydropower generation is critical for dam management. This study develops a framework based on ensemble climate models and ensemble machine learning methods to assess the projected impacts of CC on inflow to the reservoir and hydropower generation at the Nangbeto Hydropower plant in WA. Inflow to reservoir and energy generation for the future (2020–2099) is modeled using climate models output data from Coordinated Regional Downscaling Experiment to produce a publicly accessible hydropower dataset from 1980 to 2099. The bias-adjusted ensemble mean of eleven climate models for representative concentration pathways (RC4.5 and RCP8.5) are used. The added value of this approach is to use fewer input data (temperature and precipitation) while focusing on their lagged effect on inflow and energy. Generally, the model output strongly correlates with the observation (1986–2005) with a Pearson correlation of 0.86 for energy and 0.82 for inflow while the mean absolute error is 2.97% for energy and 9.73% for inflow. The results reveals that both inflow and energy simulated over the future periods (2020–2039, 2040–2059, 2060–2079, and 2080–2099) will decrease relative to the historical period (1986–2005) for both RCPs in the range of (2.5–20.5% and 1–8.5% for inflow and energy, respectively), at annual, monthly and seasonal time scales. Therefore, these results should be considered by decision-makers when assessing the best option for the energy mix development plan

Technological advances in prospecting sites for pumped hydro energy storage

In Kabo-Bah, A. T.; Diawuo, F. A.; Antwi, E. O. (Eds.). Pumped hydro energy storage for hybrid systems. London, UK: Academic PressThis chapter provides a survey of pumped hydroelectric energy storage (PHES) in terms of the factors considered in the site selection process: geographic, social, economic, and environmental. Due to the number and complexity of factors considered for this purpose, a multicriteria decision-making model is often used during the selection process. From our study, it is observed that the implementation of a PHES project may come with several environmental concerns, that is land and water requirements, impacts on the fishery industry, aquatic habitat, cultural, historical as well as natural. However, we also observed that many of these concerns are being addressed with improvement in PHES technology

Technological advances in prospecting sites for pumped hydro energy storage

This chapter provides a survey of pumped hydroelectric energy storage (PHES) in terms of the factors considered in the site selection process: geographic, social, economic, and environmental. Due to the number and complexity of factors considered for this purpose, a multicriteria decision-making model is often used during the selection process. From our study, it is observed that the implementation of a PHES project may come with several environmental concerns, that is land and water requirements, impacts on the fishery industry, aquatic habitat, cultural, historical as well as natural. However, we also observed that many of these concerns are being addressed with improvement in PHES technology

Climate and extreme rainfall events in the Mono river basin (West Africa): investigating future changes with Regional Climate Models.

27 pagesInternational audienceThis study characterizes the future changes in extreme rainfall and air temperature in the Mono river basin where the main economic activity is weather dependent and local populations are highly vulnerable to natural hazards, including flood inundations. Daily precipitation and temperature from observational datasets and Regional Climate Models (RCMs) output from REMO, RegCM, HadRM3, and RCA were used to analyze climatic variations in space and time, and fit a GEV model to investigate the extreme rainfalls and their return periods. The results indicate that the realism of the simulated climate in this domain is mainly controlled by the choice of the RCMs. These RCMs projected a 1 to 1.5 °C temperature increase by 2050 while the projected trends for cumulated precipitation are null or very moderate and diverge among models. Contrasting results were obtained for the intense rainfall events, with RegCM and HadRM3 pointing to a significant increase in the intensity of extreme rainfall events. The GEV model is well suited for the prediction of heavy rainfall events although there are uncertainties beyond the 90th percentile. The annual maxima of daily precipitation will also increase by 2050 and could be of benefit to the ecosystem services and socioeconomic activities in the Mono river basin but could also be a threat